Osteosarcoma is the most common primary malignant bone tumour in children and adolescents, yet survival rates have not improved in over 40 years. All patients receive the same chemotherapy initially, then the bony tumour is removed. The same chemo is then given for a few more months. Sadly, more than one-third of young people relapse and most die of their disease. This one-size-fits-all treatment strategy has changed little in decades. There is still no reliable way to predict which children who are going to relapse or to provide them with any alternative treatment strategy.
It is becoming increasingly clear that each patient’s cancer is composed of, not the same, but many different types of cells with different capabilities to survive the stress of chemotherapy, and then later cause relapse. The major challenge is finding these small groups of cancer cells, driven by genes or signals which are indispensable for their chemotherapy resistance. Precision medicine programs like ZERO have shown that detailed molecular characterisation of cancer cells can lead to effective therapy in high-risk child cancer. Once we know what’s causing the chemo-resistance, treatment can be redirected toward this vulnerability in a personalised therapeutic approach.
We have used cutting-edge single cell technologies to compare osteosarcoma patient specimens taken before and after chemotherapy, like gazing through a window at the detailed workings of the cancer cells. With this approach, we have been able to define driver genes responsible for chemo-resistance and use novel inhibitor drugs combined with chemotherapy to kill off these persistent chemo-resistant cells.
In other cancer types, we and others, have shown that diagnostic tests which identify high risk of relapse early in the treatment program, can allow a change to more intensive chemotherapy which improves cure rates. Here we want to further develop this single cancer cell diagnostic test in studies of a larger group of osteosarcoma patients using novel AI-driven analyses to discover more effective combination drug therapies for young people at high risk of relapse. We hope to be able to simultaneously identify each patient’s risk of relapse, the nature of the resistance factors and a therapeutic strategy to eradicate the resistant cells. If successful, these studies will form the basis of a future national clinical trial.